1. Field of the Invention
The present invention relates generally to a pattern recognition system for use, for instance, in a voice recognition system, and more particularly to a pattern recognition system which issues a category code corresponding to the nearest reference template to a characteristic pattern obtained from input signal.
2. Description of the Prior Art
In recent years, development of a pattern recognition system for the purpose of a human-machine system input means has been vigorously pursued. For instance, by recognizing a pattern of a human voice which is a source of most natural information generation, great developments are expected in input means of human-machine system, and hitherto various proposals have been made.
Hereafter, a conventional voice pattern recognition system is described with reference to FIG. 1 which is a block diagram of a configuration of a conventional system. The conventional voice pattern recognition system comprises a feature extracting part 1, a reference template memory part 2, a computation part 3, an averaging part 4 and a recognition part 5.
The conventional voice pattern recognition system configurated as shown in FIG. 1 operates as follows: Input signal IS given to the feature extracting part 1 is converted into a time sequence of characteristic patterns. Computation part 3 receives the output of the feature extracting part 1, and carries out matching computation by using multiple reference templates for each categories. The averaging part 4 makes an average of a smallest k distances for each group of results of the matching computations. Recognition part 5 makes a recognition result output, that is, the category code corresponding to the above-mentioned reference templates group having nearest average value of distance among the averaged results of the above-mentioned averaging part 4.
However, in the above-mentioned conventional configuration, though recognition accuracy rate for the above-mentioned characteristic pattern can be improved by increasing a number N of reference templates for each category and a number k of distances to be averaged by the averaging part 4, the time required for recognition in such an increased number of reference templates as well as the number k of the distances to be averaged becomes undesirably long and large. That is, in comparison with a simplest case where only one reference template for each category is provided (N=1, K=1), the above-mentioned system requires such a long time for matching computation as N-times, besides needing one averaging computation.
Furthermore, as the number M of categories increases, time required for recognition is increased to M-times of the above-mentioned case. This is a further undesirable problem.
Therefore, there is a demand for a pattern recognition system capable of recognizing input pattern with a high speed processing and a high recognition accuracy.